Spatiotemporal dynamics in spiking recurrent neural networks using modified-full-FORCE on EEG signals.

ABSTRACT: Methods on modelling the human brain as a Complex System have increased remarkably in the literature as researchers seek to understand the underlying foundations behind cognition, behaviour, and perception. Computational methods, especially Graph Theory-based methods, have recently contributed significantly in understanding the wiring connectivity of the brain, modelling it as a set of nodes connected by edges. Therefore, the brain's spatiotemporal dynamics can be holistically studied by considering a network, which consists of many neurons, represented by nodes. Various models have been proposed for modelling such neurons. A recently proposed method in training such networks, called full-Force, produces networks that perform tasks with fewer neurons and greater noise robustness than previ

SUBMITTER: Ioannides G 

PROVIDER: S-EPMC8861015 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature